建立連結

將各種不同的流程無縫整合為一個工作流程

  • 整合最新的影像、治療計畫及放射治療技術，盡在單一平台。
  • 透過 RT Peer Review促進更加和諧靈活的同儕協作
  • 透過 RapidPlan 分享最佳做法，並為社群做出貢獻
  • 使用 AI-Rad Companion Organs RT 結合 AI 輪廓描繪與自動化工作流程*
  • 簡化部門或機構之間的資料和使用者權限協調

Control

Bringing people, systems, and workflows together

  • Connect care teams, systems, and workflows across technologies, sites, and treatment approaches
  • Support treatment continuity with the optional Backup Planner, enabling efficient plan conversion across machines, techniques, and energies
  • Maintain flexibility across current and next-generation treatment delivery systems, including Accela
  • Benefit from GPU-enabled optimization algorithms that help accelerate treatment plan generation
  • Tailor planning workflows with scripting and automation tools to support institutional needs

信心

增強自主能力，使您對規劃治療計畫更有信心

  • RapidArc Dynamic 讓您更快達成臨床目標
  • SRS 使用單一等中心點和 HyperArc 高解析度放射治療
  • 使用 SBRT NTO 簡化複雜的 SBRT 治療規劃
  • 使用Plan Checker自訂和簡化治療計劃檢查流程，以符合科室標準
  • 透過增強的葉片建模功能 (ELM) 體驗更高水準的精確度

AI Contouring — Integrated in Eclipse

High-quality, deep learning-driven structure delineation directly within your treatment planning workflow

  • Automatically generates contours from CT and MRI images for over 200 anatomical structures — including organs-at-risk, lymph nodes, and brain metastases
  • Built on multiple clinical guidelines (RTOG, ESTRO, DAHANCA, and more) for consistent, evidence-based results
  • Seamlessly integrated within Eclipse, with no additional hardware, no separate platform, and single vendor support
  • Validated by leading institutions2,3 worldwide, with auto contouring results on par with expert physicians4

輔助 Eclipse

治療投照

Explore the entire Digital Oncology portfolio

我們可協助您建立聯繫

我們的專員可協助您將瓦里安系統整合至您的工作流程中。

若您是既有客戶且需要產品支援，請造訪客戶支援頁面

†獲 CE 標誌 (歐洲合格認證)。 510(k) 待處理。 本產品並未在美國或所有市場提供，且不保證商品化或功能可用性。

*AI-Rad Companion Organ RT 是西門子醫療設備公司的產品，也是西門子資料設備公司在部分國家/地區的註冊商標。

  1. Putz, F. Is AI-powered tumor autocontouring ready for clinical use? Evaluation of Siemens Healthineers research prototype for the autosegmentation of brain metastases. Poster presented at DEGRO; Jun 2025, Dresden, Germany. Datasets: 101 patients; 391 lesions; 1.5T MRI series T1-SPACE. University of Erlangen-Nuremberg.
  2. Tezcanli, E. Evaluation of a Deep Learning Contouring Algorithm for Target Delineation in HyperArc Radiosurgery. Webinar, Oct 2025. Datasets: 10 patients; 82 lesions. Acibadem University.